45 Key HR Metrics And Data Management Best Practices

“What gets measured gets managed.” - Peter Drucker

Organizations track HR metrics to better understand their workforce and measure the effectiveness of their HR function.

I’ve been an HR professional for nearly 20 years, and one of the core bedrocks of my approach in every role has been to clearly understand the metrics that underpin what I’m trying to achieve. 

Developing a solid grounding with your HR metrics gives you the essential base to build on more sophisticated analysis as you develop your capabilities.

Here I’ll provide example HR metrics and lay out a few guiding principles that will make your data journey more efficient.

What Are HR Metrics?

HR metrics are key data points about your workforce, for example demographics, and the activities of your HR function, such as recruitment.

HR metrics are key data points about your workforce, for example demographics, and the activities of your HR function, for example recruitment. They’re used to track performance against organizational objectives and guide strategy.

HR metrics are the facts of your organization. They aren't opinions, they aren't estimates, they're the facts about the people in your organization. 

Alone they don’t tell a story but, once you combine them with richer information and other business data and metrics, you can build an accurate picture of what drives success.

45 key human resources metrics you should Track and how to assess them

Headcount

Aim to show the number of employees you have (permanent and contractors if that’s relevant for your business) and where they’re based, in which office, and in which executive department they sit.

5 Attrition and retention rate metrics

1. Turnover rate. How many people are leaving and from which location/executive department/demographic?
2. Why are they leaving—voluntary/non-voluntary? 
3. Average tenure of leavers 
4. What is your attrition rate? (and your calculation needs to be consistent here). My suggestion for attrition is: 
   
   Number of leavers over last 12 months / ((permanent headcount 12 months ago + permanent headcount today) / 2)
   
   Many people prefer to have attrition measuring just voluntary leavers, both measures are needed and you can choose what is the headline method.
5. What is your retention rate? Normally calculated annually:
   
   Number of individual employees who remained employed for entire measurement period / number of employees at start of measurement period x 100

10 Recruitment metrics

1. How many people are you hiring and in what location/executive department?  
2. Time to fill
3. Best sources of hire e.g. referral 
4. How costly is hiring e.g. average cost per hire
5. Vacancies per recruiter
6. Number of applications 
7. Number of interviews
8. Job offer acceptance rate (%)  
9. LinkedIn (other social?) followers 
10. Glassdoor rating.

4 Demographics metrics. Who are your people?

1. Gender split
2. Nationality
3. Tenure
4. Diversity measures such as age, education level, ethnicity. Can further split this by location/executive department (depending on what you have today and what’s important to your organization).

5 Organizational measures

1. Percentage of managers
2. Span of control
3. Number of people at each layer in the business
4. Number of open vacancies
5. Growth over time.

4 Absenteeism metrics

1. How many holidays used and remaining by individuals and by the business
2. Sicknesses
3. Work-from-home/abroad arrangements 
4. Taken/left from allowance.

8 Learning and development metrics

1. Hours of learning
2. Desired change e.g. behavior or business metric
3. Skill improvement
4. Knowledge uptake
5. Number of mentorships
6. Mandatory training program completion rate
7. Type of learning (online vs classroom)
8. Training budget spent.

2 Performance metrics

1. Percentage of employees with goals
2. Performance/potential/loss impact rating by location/executive function.

4 Compensation metrics

1. Total payroll expenditure
2. Payroll expenditure as % of revenue
3. Gender pay gap
4. Benefit participation rates.

3 Engagement metrics

This depends on what employee engagement tools (if any) you have in place for engagement and the score is dependent on that methodology.

1. Employee engagement score by location and executive department
2. Intent to stay
3. Net promoter score.

These may not be the perfect set of metrics for your organization but they’re a starting point to get you thinking about what’s right.

While some of these have very obvious calculation methods, others are more open to interpretation.

The main thing to be wary of is being consistent and clear about how a metric is calculated and therefore what it means.

How To Establish Your Key HR Metrics

The key HR metrics organizations keep track of vary from business to business.

Here are some pointers for deciding which metrics will take priority.

Align with organizational goals 

The metrics you track will feed directly into your HR KPIs, and these should align with the broader goals and objectives of the organization.

For example, if you’re scaling and need to grow headcount, time-to-hire and cost-per-hire will likely be metrics you pay close attention to.

Learn what interests your stakeholders

HR metrics aren’t just for the HR departments. Senior leadership, as well as individual managers and even individual contributors, can benefit from this information.

When you’ve started to collect reliable employee data, share it with your key stakeholders and discover what’s of interest to them.

Maybe you find a particular department is having an issue with new hires leaving in their first year. Someone's likely to be interested in this!

One handy method I borrowed from marketing is to create internal personas for each of your stakeholder groups. This will help you think about who needs what information and how to present it.

How To Collect HR Metrics

Your HR data will likely live in a few different places, including your HR database, learning management system, applicant tracking system, employee engagement software, or even spreadsheets.

There is also specialist people analytics software to help you collect and analyze quantitative and qualitative data.

As stated above, for each of your metrics you need to be clear about what it is, what the data source is, how it's calculated, and how we would audit the underlying process that supports it.

So, if we’re measuring the number of leavers in a month, this could be:

• What is it? Permanent employees leaving location/function/company/team in a given calendar month.
• Data source. HRIS report—leavers by month.
• How it’s calculated. Permanent employees leaving from 1st-last day of the month (garden leave calculated as last day of employment). Any leavers who are missed we recalculate for previous months and make a note in the metrics pack.
• Underlying processes. Check payroll is aligned with leavers, any leaver checklists you might have, and redundancy lists. Revisit any mistakes from previous months with clear trails back to source so you can see what went wrong.

By ensuring you have this level of rigor with each metric you will build stable, strong underlying data and processes that support the development of a more mature analytics capability in the future, as well as solid processes that underpin the whole HR team.

Presenting HR Metrics

The next challenge you have is how to share this information, visualising your data is critical because as you gather this data and share it over time it tells a story. 

Are you growing as an organization (are you growing quickly enough), is your gender pay gap widening?

These are all comparable measures that are only possible by collating and reporting on this data regularly.

In terms of how to visualize the data, here are some pointers.

• Use graphs rather than a table of numbers where possible, Excel is a great tool here
• Set it up so you can see progress over time (monthly or quarterly)
• Use your company color scheme and presentation layout
• Add simple commentary to the presentation to explain anything that isn’t clear or to contextualize the change.

The personas idea I mentioned earlier can help you with this.

Principles For Accurate HR Metrics

I once joined a company to establish the talent acquisition function. For the first 6 months, I gathered as much data as I could on our hiring practices: source/cost/time/location/function/role type—all of the typical hiring data you might expect.

I put this in various presentations to make the case for the changes I felt were necessary. Then, one day, we had a problem.

On an investor call, someone asked a question about our headcount because the numbers didn't look right. Guess what, they were right and we were wrong!

The problem landed on my desk, I can't remember why but likely because I'd tried to use data to drive action, but I do remember sitting in a stuffy meeting room for what felt like an eternity tracing through what data that was sent to our finance team, its origin, and its accuracy to try and find out how it could be incorrect in our public statements.

It came down to 2 simple problems:

1) We sent them data from our (very old, very rubbish) HR system on a set date and it transpired that people updated the system with new starters and leavers in time for payroll and not in time for this report. So the data was never correct, it couldn't be.

2) We sent them an aggregated headcount that included contractors (as that was the report that had always been sent) and nobody, as far as I could tell, ever questioned or asked what the numbers meant.

There were several other headaches as well but these were the two key points. We ended up refreshing our onboarding and offboarding processes, redoing how we calculated the headcount that we shared, and unifying those processes.

I know this seems basic but it’s a good example of how easily these things can go awry. So, some key principles to help you collect accurate data:

1) Be clear about what the metric is

2) Be clear about how it’s calculated and what your data sources are

3) Be clear that you understand and can audit the processes that feed into the metric.

Once you have a stable set of metrics, you then have the opportunity to combine and interpret them to create a picture of what’s happening in your organization and what you might want to do to change them. 

For example, if ‘time to hire’ and the recruiter’s average number of job requisitions are climbing, is more recruiters a potential solution?

Use HR Metrics To Guide Decision-making

Your HR metrics are key to both tracking and enacting change. But complex HR data analysis can only be achieved with good data—following these steps will set you up perfectly for that:

• Agree your metrics
• Be clear on calculation and make sure it’s auditable and consistent
• Display them clearly
• Repeat consistently.

If you do this, you’ll build credibility in using HR data and set your business up for more detailed analysis. 

If you're looking to learn more about HR analytics to fuel your efforts here, check out this list of HR analytics courses that can help you along the way.

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FAQs

Why do we need HR metrics?

People are normally the biggest cost and a critical success factor in the continued success of every business.

As we measure our business growth in terms of the number of customers, revenue, profit and value, it makes perfect sense to measure the people elements at the same time. 

They’ll enable data-driven decision-making and help you fine-tune your HR processes and create exciting new initiatives.

What are soft HR metrics?

Much of the data outlined above is hard data i.e. quantitative. Soft data is qualitative, meaning that it’s difficult to represent numerically. Soft data includes information collected from observations, interviews, surveys, and sentiment analysis. It adds an extra layer of depth to the quantitative data and can be just as valuable.

Which are the most important HR Metrics?

As discussed above, the most important HR metrics will vary from organization to organization. That being said, employee retention, turnover, time-to-hire, and demographics are generally universally valuable.